def validate_trading(self, order, bar): order_book_id = order.order_book_id trading_date = ExecutionContext.get_current_trading_dt().date() if bar.isnan: """ 只有未上市/已退市,对应的bar才为NaN """ instrument = ExecutionContext.get_instrument(order_book_id) if trading_date < instrument.listed_date.date(): order._mark_rejected( _("Order Rejected: {order_book_id} is not listed!").format( order_book_id=order_book_id, )) elif trading_date > instrument.de_listed_date.date(): order._mark_rejected( _("Order Rejected: {order_book_id} has been delisted!"). format(order_book_id=order_book_id, )) else: order._mark_rejected( _("Order Rejected: {order_book_id} is not trading!"). format(order_book_id=order_book_id, )) return False elif not bar.is_trading: """ 如果bar.is_trading为False,还需要判断是否为停盘,如果不是停牌,则说明交易量为0. """ if bar.suspended: order._mark_rejected( _("Order Rejected: {order_book_id} is suspended!").format( order_book_id=order_book_id, )) return False return True
def submit_order(self, order): if order.position_effect == POSITION_EFFECT.MATCH: raise NotImplementedError( _("unsupported position_effect {}").format( order.position_effect)) account = self._env.get_account(order.order_book_id) self._env.event_bus.publish_event( Event(EVENT.ORDER_PENDING_NEW, account=account, order=order)) if order.position_effect == POSITION_EFFECT.EXERCISE: return self._open_exercise_orders.append(order) if order.is_final(): return if self._env.config.base.frequency == '1d' and not self._match_immediately: if ExecutionContext.phase() == EXECUTION_PHASE.OPEN_AUCTION: self._open_orders.append((account, order)) order.active() else: self._delayed_orders.append((account, order)) return if ExecutionContext.phase() == EXECUTION_PHASE.OPEN_AUCTION: self._open_auction_orders.append((account, order)) else: self._open_orders.append((account, order)) order.active() self._env.event_bus.publish_event( Event(EVENT.ORDER_CREATION_PASS, account=account, order=order)) if self._match_immediately: self._match()
def __getitem__(self, key): if not isinstance(key, six.string_types): raise patch_user_exc(ValueError('invalid key {} (use order_book_id please)'.format(key))) instrument = self._data_proxy.instruments(key) if instrument is None: raise patch_user_exc(ValueError('invalid order book id or symbol: {}'.format(key))) order_book_id = instrument.order_book_id try: return self._cache[order_book_id] except KeyError: try: if not self._dt: return BarObject(instrument, NANDict, self._dt) if ExecutionContext.phase() == EXECUTION_PHASE.OPEN_AUCTION: bar = self._data_proxy.get_open_auction_bar(order_book_id, self._dt) else: bar = self._data_proxy.get_bar(order_book_id, self._dt, self._frequency) except PermissionError: raise except Exception as e: system_log.exception(e) raise patch_user_exc(KeyError(_(u"id_or_symbols {} does not exist").format(key))) if bar is None: return BarObject(instrument, NANDict, self._dt) else: self._cache[order_book_id] = bar return bar
def init(self): if self._init: with ExecutionContext(EXECUTION_PHASE.ON_INIT): with ModifyExceptionFromType(EXC_TYPE.USER_EXC): self._init(self._user_context) Environment.get_instance().event_bus.publish_event( Event(EVENT.POST_USER_INIT))
def before_trading_(self, event): with ExecutionContext(EXECUTION_PHASE.BEFORE_TRADING): self._stage = 'before_trading' for day_rule, time_rule, func in self._registry: if day_rule() and time_rule(): with ModifyExceptionFromType(EXC_TYPE.USER_EXC): func(self._ucontext, None) self._stage = None
def handle_tick(self, event): if self._force_run_before_trading: self.before_trading(event) else: tick = event.tick with ExecutionContext(EXECUTION_PHASE.ON_TICK): with ModifyExceptionFromType(EXC_TYPE.USER_EXC): self._handle_tick(self._user_context, tick)
def handle_bar(self, event): if self._force_run_before_trading: self.before_trading(event) else: bar_dict = event.bar_dict with ExecutionContext(EXECUTION_PHASE.ON_BAR): with ModifyExceptionFromType(EXC_TYPE.USER_EXC): self._handle_bar(self._user_context, bar_dict)
def next_bar_(self, event): bars = event.bar_dict with ExecutionContext(EXECUTION_PHASE.SCHEDULED): self._current_minute = self._minutes_since_midnight(self._ucontext.now.hour, self._ucontext.now.minute) for day_rule, time_rule, func in self._registry: if day_rule() and time_rule(): with ModifyExceptionFromType(EXC_TYPE.USER_EXC): func(self._ucontext, bars) self._last_minute = self._current_minute
def end(self): if not self._end: return with ExecutionContext(EXECUTION_PHASE.FINALIZED): with ModifyExceptionFromType(EXC_TYPE.USER_EXC): self._end(self._user_context) Environment.get_instance().event_bus.publish_event( Event(EVENT.POST_USER_END))
def current_snapshot(id_or_symbol): """ 获得当前市场快照数据。只能在日内交易阶段调用,获取当日调用时点的市场快照数据。 市场快照数据记录了每日从开盘到当前的数据信息,可以理解为一个动态的day bar数据。 在目前分钟回测中,快照数据为当日所有分钟线累积而成,一般情况下,最后一个分钟线获取到的快照数据应当与当日的日线行情保持一致。 需要注意,在实盘模拟中,该函数返回的是调用当时的市场快照情况,所以在同一个handle_bar中不同时点调用可能返回的数据不同。 如果当日截止到调用时候对应股票没有任何成交,那么snapshot中的close, high, low, last几个价格水平都将以0表示。 :param str order_book_id: 合约代码或简称 :return: :class:`~Snapshot` :example: 在handle_bar中调用该函数,假设策略当前时间是20160104 09:33: .. code-block:: python3 :linenos: [In] logger.info(current_snapshot('000001.XSHE')) [Out] 2016-01-04 09:33:00.00 INFO Snapshot(order_book_id: '000001.XSHE', datetime: datetime.datetime(2016, 1, 4, 9, 33), open: 10.0, high: 10.025, low: 9.9667, last: 9.9917, volume: 2050320, total_turnover: 20485195, prev_close: 9.99) """ env = Environment.get_instance() frequency = env.config.base.frequency order_book_id = assure_order_book_id(id_or_symbol) dt = env.calendar_dt if env.config.base.run_type == RUN_TYPE.BACKTEST: if ExecutionContext.phase() == EXECUTION_PHASE.BEFORE_TRADING: dt = env.data_proxy.get_previous_trading_date( env.trading_dt.date()) return env.data_proxy.current_snapshot(order_book_id, "1d", dt) elif ExecutionContext.phase() == EXECUTION_PHASE.AFTER_TRADING: return env.data_proxy.current_snapshot(order_book_id, "1d", dt) # PT、实盘直接取最新快照,忽略 frequency, dt 参数 return env.data_proxy.current_snapshot(order_book_id, frequency, dt)
def current_snapshot(id_or_symbol): """ 获得当前市场快照数据。只能在日内交易阶段调用,获取当日调用时点的市场快照数据。 市场快照数据记录了每日从开盘到当前的数据信息,可以理解为一个动态的day bar数据。 在目前分钟回测中,快照数据为当日所有分钟线累积而成,一般情况下,最后一个分钟线获取到的快照数据应当与当日的日线行情保持一致。 需要注意,在实盘模拟中,该函数返回的是调用当时的市场快照情况,所以在同一个handle_bar中不同时点调用可能返回的数据不同。 如果当日截止到调用时候对应股票没有任何成交,那么snapshot中的close, high, low, last几个价格水平都将以0表示。 :param str order_book_id: 合约代码或简称 :return: :class:`~Snapshot` :example: 在handle_bar中调用该函数,假设策略当前时间是20160104 09:33: .. code-block:: python3 :linenos: [In] logger.info(current_snapshot('000001.XSHE')) [Out] 2016-01-04 09:33:00.00 INFO Snapshot(order_book_id: '000001.XSHE', datetime: datetime.datetime(2016, 1, 4, 9, 33), open: 10.0, high: 10.025, low: 9.9667, last: 9.9917, volume: 2050320, total_turnover: 20485195, prev_close: 9.99) """ env = Environment.get_instance() frequency = env.config.base.frequency order_book_id = assure_order_book_id(id_or_symbol) dt = env.calendar_dt if env.config.base.run_type == RUN_TYPE.BACKTEST: if ExecutionContext.phase() == EXECUTION_PHASE.BEFORE_TRADING: dt = env.data_proxy.get_previous_trading_date(env.trading_dt.date()) return env.data_proxy.current_snapshot(order_book_id, "1d", dt) elif ExecutionContext.phase() == EXECUTION_PHASE.AFTER_TRADING: return env.data_proxy.current_snapshot(order_book_id, "1d", dt) # PT、实盘直接取最新快照,忽略 frequency, dt 参数 return env.data_proxy.current_snapshot(order_book_id, frequency, dt)
def order_pipeline(self, account, order): order_book_id = order.order_book_id bar_dict = ExecutionContext.get_current_bar_dict() portfolio = account.portfolio position = portfolio.positions[order_book_id] bar = bar_dict[order_book_id] if not self.validate_trading(order, bar): return False if not self.validate_available_cash(order, account, bar): return False if not self.validate_available_position(order, position): return False return True
def mavg(self, intervals, frequency='1d'): if frequency == 'day': frequency = '1d' if frequency == 'minute': frequency = '1m' # copy form history env = Environment.get_instance() dt = env.calendar_dt if (env.config.base.frequency == '1m' and frequency == '1d') or ExecutionContext.phase() == EXECUTION_PHASE.BEFORE_TRADING: # 在分钟回测获取日线数据, 应该推前一天 dt = env.data_proxy.get_previous_trading_date(env.calendar_dt.date()) bars = env.data_proxy.fast_history(self._instrument.order_book_id, intervals, frequency, 'close', dt) return bars.mean()
def _history_bars(self, order_book_id, bar_count, freq, dt): if self.fetch_data_by_api and ExecutionContext.phase() in ( EXECUTION_PHASE.BEFORE_TRADING, EXECUTION_PHASE.ON_BAR, EXECUTION_PHASE.ON_TICK, EXECUTION_PHASE.AFTER_TRADING, EXECUTION_PHASE.SCHEDULED): bars = history_bars( order_book_id, bar_count, freq, fields=None) else: bars = self.rqalpha_env.data_proxy.history_bars( order_book_id, bar_count, freq, field=["datetime", "open", "high", "low", "close", "volume"], dt=dt) return bars
def vwap(self, intervals, frequency='1d'): if frequency == 'day': frequency = '1d' if frequency == 'minute': frequency = '1m' # copy form history env = Environment.get_instance() dt = env.calendar_dt if (env.config.base.frequency == '1m' and frequency == '1d') or ExecutionContext.phase() == EXECUTION_PHASE.BEFORE_TRADING: # 在分钟回测获取日线数据, 应该推前一天 dt = env.data_proxy.get_previous_trading_date(env.calendar_dt.date()) bars = env.data_proxy.fast_history(self._instrument.order_book_id, intervals, frequency, ['close', 'volume'], dt) sum = bars['volume'].sum() if sum == 0: # 全部停牌 return 0 return np.dot(bars['close'], bars['volume']) / sum
def run(config, source_code=None, user_funcs=None): env = Environment(config) persist_helper = None init_succeed = False mod_handler = ModHandler() try: # avoid register handlers everytime # when running in ipython set_loggers(config) basic_system_log.debug("\n" + pformat(config.convert_to_dict())) if source_code is not None: env.set_strategy_loader(SourceCodeStrategyLoader(source_code)) elif user_funcs is not None: env.set_strategy_loader(UserFuncStrategyLoader(user_funcs)) else: env.set_strategy_loader(FileStrategyLoader(config.base.strategy_file)) env.set_global_vars(GlobalVars()) mod_handler.set_env(env) mod_handler.start_up() if not env.data_source: env.set_data_source(BaseDataSource(config.base.data_bundle_path)) env.set_data_proxy(DataProxy(env.data_source)) Scheduler.set_trading_dates_(env.data_source.get_trading_calendar()) scheduler = Scheduler(config.base.frequency) mod_scheduler._scheduler = scheduler env._universe = StrategyUniverse() _adjust_start_date(env.config, env.data_proxy) _validate_benchmark(env.config, env.data_proxy) # FIXME start_dt = datetime.datetime.combine(config.base.start_date, datetime.datetime.min.time()) env.calendar_dt = start_dt env.trading_dt = start_dt broker = env.broker assert broker is not None env.portfolio = broker.get_portfolio() env.benchmark_portfolio = create_benchmark_portfolio(env) event_source = env.event_source assert event_source is not None bar_dict = BarMap(env.data_proxy, config.base.frequency) env.set_bar_dict(bar_dict) if env.price_board is None: from .core.bar_dict_price_board import BarDictPriceBoard env.price_board = BarDictPriceBoard() ctx = ExecutionContext(const.EXECUTION_PHASE.GLOBAL) ctx._push() env.event_bus.publish_event(Event(EVENT.POST_SYSTEM_INIT)) scope = create_base_scope() scope.update({ "g": env.global_vars }) apis = api_helper.get_apis() scope.update(apis) scope = env.strategy_loader.load(scope) if env.config.extra.enable_profiler: enable_profiler(env, scope) ucontext = StrategyContext() user_strategy = Strategy(env.event_bus, scope, ucontext) scheduler.set_user_context(ucontext) if not config.extra.force_run_init_when_pt_resume: with run_with_user_log_disabled(disabled=config.base.resume_mode): user_strategy.init() if config.extra.context_vars: for k, v in six.iteritems(config.extra.context_vars): setattr(ucontext, k, v) if config.base.persist: persist_provider = env.persist_provider persist_helper = PersistHelper(persist_provider, env.event_bus, config.base.persist_mode) persist_helper.register('core', CoreObjectsPersistProxy(scheduler)) persist_helper.register('user_context', ucontext) persist_helper.register('global_vars', env.global_vars) persist_helper.register('universe', env._universe) if isinstance(event_source, Persistable): persist_helper.register('event_source', event_source) persist_helper.register('portfolio', env.portfolio) if env.benchmark_portfolio: persist_helper.register('benchmark_portfolio', env.benchmark_portfolio) for name, module in six.iteritems(env.mod_dict): if isinstance(module, Persistable): persist_helper.register('mod_{}'.format(name), module) # broker will restore open orders from account if isinstance(broker, Persistable): persist_helper.register('broker', broker) persist_helper.restore() env.event_bus.publish_event(Event(EVENT.POST_SYSTEM_RESTORED)) init_succeed = True # When force_run_init_when_pt_resume is active, # we should run `init` after restore persist data if config.extra.force_run_init_when_pt_resume: assert config.base.resume_mode == True with run_with_user_log_disabled(disabled=False): user_strategy.init() from .core.executor import Executor Executor(env).run(bar_dict) if env.profile_deco: output_profile_result(env) except CustomException as e: if init_succeed and env.config.base.persist and persist_helper: persist_helper.persist() code = _exception_handler(e) mod_handler.tear_down(code, e) except Exception as e: if init_succeed and env.config.base.persist and persist_helper: persist_helper.persist() exc_type, exc_val, exc_tb = sys.exc_info() user_exc = create_custom_exception(exc_type, exc_val, exc_tb, config.base.strategy_file) code = _exception_handler(user_exc) mod_handler.tear_down(code, user_exc) else: result = mod_handler.tear_down(const.EXIT_CODE.EXIT_SUCCESS) system_log.debug(_(u"strategy run successfully, normal exit")) return result
def run(config, source_code=None, user_funcs=None): env = Environment(config) persist_helper = None init_succeed = False mod_handler = ModHandler() #初始化模块处理器,包含list和dict,存储模块名和配置信息 try: # avoid register handlers everytime # when running in ipython set_loggers(config) basic_system_log.debug("\n" + pformat(config.convert_to_dict())) if source_code is not None: env.set_strategy_loader(SourceCodeStrategyLoader(source_code)) elif user_funcs is not None: env.set_strategy_loader(UserFuncStrategyLoader(user_funcs)) else: #将文件路径赋予env中的属性 env.set_strategy_loader( FileStrategyLoader(config.base.strategy_file)) env.set_global_vars(GlobalVars()) mod_handler.set_env(env) #根据config读取mod,并绑定到env变量 mod_handler.start_up() #运行每个mod的启动函数,传入env.config,以及mod自己的config,后者冗余? if not env.data_source: env.set_data_source(data_k_bar) #BaseDataSource:读取bar数据,存储到对象属性中 env.set_data_proxy(DataProxy(env.data_source)) Scheduler.set_trading_dates_(env.data_source.get_trading_calendar()) scheduler = Scheduler(config.base.frequency) mod_scheduler._scheduler = scheduler env._universe = StrategyUniverse() _adjust_start_date(env.config, env.data_proxy) _validate_benchmark(env.config, env.data_proxy) # FIXME start_dt = datetime.datetime.combine(config.base.start_date, datetime.datetime.min.time()) env.calendar_dt = start_dt env.trading_dt = start_dt broker = env.broker assert broker is not None env.portfolio = broker.get_portfolio() env.benchmark_portfolio = create_benchmark_portfolio(env) event_source = env.event_source assert event_source is not None #包含 data_proxy, frequency ... bar_dict = BarMap(env.data_proxy, config.base.frequency) env.set_bar_dict(bar_dict) #本地历史行情对象,包含所有 #获取最新价格 if env.price_board is None: from .core.bar_dict_price_board import BarDictPriceBoard env.price_board = BarDictPriceBoard() ctx = ExecutionContext(const.EXECUTION_PHASE.GLOBAL) ctx._push() env.event_bus.publish_event(Event(EVENT.POST_SYSTEM_INIT)) #全局文件路径、文件名、log入口等,作为参数传递给编译 scope = create_base_scope() scope.update({"g": env.global_vars}) #用户策略可调用的api,包括历史行情、下单函数等 apis = api_helper.get_apis() scope.update(apis) #加载用户策略文件,并执行? scope = env.strategy_loader.load(scope) #是否启用性能分析 if env.config.extra.enable_profiler: enable_profiler(env, scope) #生成用户策略运行时上下文变量 ucontext = StrategyContext() user_strategy = Strategy(env.event_bus, scope, ucontext) scheduler.set_user_context(ucontext) #没有若策略运行时数据持久化,运行用户init if not config.extra.force_run_init_when_pt_resume: with run_with_user_log_disabled(disabled=config.base.resume_mode): user_strategy.init() #是否在参数中存在用户输入的运行时环境变量 if config.extra.context_vars: for k, v in six.iteritems(config.extra.context_vars): setattr(ucontext, k, v) if config.base.persist: persist_provider = env.persist_provider if persist_provider is None: raise RuntimeError( _(u"Missing persist provider. You need to set persist_provider before use persist" )) persist_helper = PersistHelper(persist_provider, env.event_bus, config.base.persist_mode) env.set_persist_helper(persist_helper) persist_helper.register('core', CoreObjectsPersistProxy(scheduler)) persist_helper.register('user_context', ucontext) persist_helper.register('global_vars', env.global_vars) persist_helper.register('universe', env._universe) if isinstance(event_source, Persistable): persist_helper.register('event_source', event_source) persist_helper.register('portfolio', env.portfolio) if env.benchmark_portfolio: persist_helper.register('benchmark_portfolio', env.benchmark_portfolio) for name, module in six.iteritems(env.mod_dict): if isinstance(module, Persistable): persist_helper.register('mod_{}'.format(name), module) # broker will restore open orders from account if isinstance(broker, Persistable): persist_helper.register('broker', broker) env.event_bus.publish_event(Event(EVENT.BEFORE_SYSTEM_RESTORED)) persist_helper.restore() env.event_bus.publish_event(Event(EVENT.POST_SYSTEM_RESTORED)) init_succeed = True #若启用回测数据持久化,恢复时重新初始化用户策略 # When force_run_init_when_pt_resume is active, # we should run `init` after restore persist data if config.extra.force_run_init_when_pt_resume: assert config.base.resume_mode == True with run_with_user_log_disabled(disabled=False): env._universe._set = set() user_strategy.init() from .core.executor import Executor Executor(env).run(bar_dict) if env.profile_deco: output_profile_result(env) except CustomException as e: if init_succeed and env.config.base.persist and persist_helper and env.config.base.persist_mode == const.PERSIST_MODE.ON_CRASH: persist_helper.persist() code = _exception_handler(e) mod_handler.tear_down(code, e) except Exception as e: if init_succeed and env.config.base.persist and persist_helper and env.config.base.persist_mode == const.PERSIST_MODE.ON_CRASH: persist_helper.persist() exc_type, exc_val, exc_tb = sys.exc_info() user_exc = create_custom_exception(exc_type, exc_val, exc_tb, config.base.strategy_file) code = _exception_handler(user_exc) mod_handler.tear_down(code, user_exc) else: if (env.config.base.persist and persist_helper and env.config.base.persist_mode == const.PERSIST_MODE.ON_NORMAL_EXIT): persist_helper.persist() result = mod_handler.tear_down(const.EXIT_CODE.EXIT_SUCCESS) system_log.debug(_(u"strategy run successfully, normal exit")) return result
def _get_bar(self, order_book_id): if ExecutionContext.phase() == EXECUTION_PHASE.OPEN_AUCTION: return self._env.data_proxy.get_open_auction_bar( order_book_id, self._env.calendar_dt) return self._env.get_bar(order_book_id)
def after_trading(self, event): with ExecutionContext(EXECUTION_PHASE.AFTER_TRADING): with ModifyExceptionFromType(EXC_TYPE.USER_EXC): self._after_trading(self._user_context)
def before_trading(self, event): self._force_run_before_trading = False with ExecutionContext(EXECUTION_PHASE.BEFORE_TRADING): with ModifyExceptionFromType(EXC_TYPE.USER_EXC): self._before_trading(self._user_context)
def handle_bar(self, event): bar_dict = event.bar_dict with ExecutionContext(EXECUTION_PHASE.ON_BAR): with ModifyExceptionFromType(EXC_TYPE.USER_EXC): self._handle_bar(self._user_context, bar_dict)
def history_bars( order_book_id, bar_count, frequency, fields=None, skip_suspended=True, include_now=False, adjust_type="pre", ): # type: (str, int, str, Optional[str], Optional[bool], Optional[bool], Optional[str]) -> np.ndarray """ 获取指定合约的历史 k 线行情,同时支持日以及分钟历史数据。不能在init中调用。 日回测获取分钟历史数据:不支持 日回测获取日历史数据 ========================= =================================================== 调用时间 返回数据 ========================= =================================================== T日before_trading T-1日day bar T日handle_bar T日day bar ========================= =================================================== 分钟回测获取日历史数据 ========================= =================================================== 调用时间 返回数据 ========================= =================================================== T日before_trading T-1日day bar T日handle_bar T-1日day bar ========================= =================================================== 分钟回测获取分钟历史数据 ========================= =================================================== 调用时间 返回数据 ========================= =================================================== T日before_trading T-1日最后一个minute bar T日handle_bar T日当前minute bar ========================= =================================================== :param order_book_id: 合约代码 :param bar_count: 获取的历史数据数量,必填项 :param frequency: 获取数据什么样的频率进行。'1d'或'1m'分别表示每日和每分钟,必填项 :param fields: 返回数据字段。必填项。见下方列表。 :param skip_suspended: 是否跳过停牌数据 :param include_now: 是否包含当前数据 :param adjust_type: 复权类型,默认为前复权 pre;可选 pre, none, post ========================= =================================================== fields 字段名 ========================= =================================================== datetime 时间戳 open 开盘价 high 最高价 low 最低价 close 收盘价 volume 成交量 total_turnover 成交额 open_interest 持仓量(期货专用) basis_spread 期现差(股指期货专用) settlement 结算价(期货日线专用) prev_settlement 结算价(期货日线专用) ========================= =================================================== :example: 获取最近5天的日线收盘价序列(策略当前日期为20160706): .. code-block:: python3 :linenos: [In] logger.info(history_bars('000002.XSHE', 5, '1d', 'close')) [Out] [ 8.69 8.7 8.71 8.81 8.81] """ order_book_id = assure_order_book_id(order_book_id) env = Environment.get_instance() dt = env.calendar_dt if frequency[-1] not in {"m", "d"}: raise RQInvalidArgument("invalid frequency {}".format(frequency)) if frequency[-1] == "m" and env.config.base.frequency == "1d": raise RQInvalidArgument("can not get minute history in day back test") if frequency[-1] == "d" and frequency != "1d": raise RQInvalidArgument("invalid frequency") if adjust_type not in {"pre", "post", "none"}: raise RuntimeError("invalid adjust_type") if frequency == "1d": sys_frequency = Environment.get_instance().config.base.frequency if (sys_frequency in ["1m", "tick"] and not include_now and ExecutionContext.phase() != EXECUTION_PHASE.AFTER_TRADING ) or (ExecutionContext.phase() in (EXECUTION_PHASE.BEFORE_TRADING, EXECUTION_PHASE.OPEN_AUCTION)): dt = env.data_proxy.get_previous_trading_date( env.trading_dt.date()) # 当 EXECUTION_PHASE.BEFORE_TRADING 的时候,强制 include_now 为 False include_now = False if sys_frequency == "1d": # 日回测不支持 include_now include_now = False if fields is None: fields = ["datetime", "open", "high", "low", "close", "volume"] return env.data_proxy.history_bars( order_book_id, bar_count, frequency, fields, dt, skip_suspended=skip_suspended, include_now=include_now, adjust_type=adjust_type, adjust_orig=env.trading_dt, )
def wrapped_handler(event): with ExecutionContext(EXECUTION_PHASE.GLOBAL): with ModifyExceptionFromType(EXC_TYPE.USER_EXC): return handler(self._user_context, event)
def run(config, source_code=None, user_funcs=None): env = Environment(config) persist_helper = None init_succeed = False mod_handler = ModHandler() try: # avoid register handlers everytime # when running in ipython set_loggers(config) init_rqdatac(getattr(config.base, 'rqdatac_uri', None)) system_log.debug("\n" + pformat(config.convert_to_dict())) env.set_strategy_loader( init_strategy_loader(env, source_code, user_funcs, config)) mod_handler.set_env(env) mod_handler.start_up() if not env.data_source: env.set_data_source( BaseDataSource(config.base.data_bundle_path, getattr(config.base, "future_info", {}))) if env.price_board is None: from rqalpha.data.bar_dict_price_board import BarDictPriceBoard env.price_board = BarDictPriceBoard() env.set_data_proxy(DataProxy(env.data_source, env.price_board)) _adjust_start_date(env.config, env.data_proxy) # FIXME start_dt = datetime.datetime.combine(config.base.start_date, datetime.datetime.min.time()) env.calendar_dt = start_dt env.trading_dt = start_dt assert env.broker is not None assert env.event_source is not None if env.portfolio is None: from rqalpha.portfolio import Portfolio env.set_portfolio( Portfolio(config.base.accounts, config.base.init_positions)) ctx = ExecutionContext(const.EXECUTION_PHASE.GLOBAL) ctx._push() env.event_bus.publish_event(Event(EVENT.POST_SYSTEM_INIT)) scope = create_base_scope() scope.update({"g": env.global_vars}) scope.update(get_strategy_apis()) scope = env.strategy_loader.load(scope) if config.extra.enable_profiler: enable_profiler(env, scope) ucontext = StrategyContext() executor = Executor(env) persist_helper = init_persist_helper(env, ucontext, executor, config) user_strategy = Strategy(env.event_bus, scope, ucontext) env.user_strategy = user_strategy env.event_bus.publish_event(Event(EVENT.BEFORE_STRATEGY_RUN)) if persist_helper: with LogCapture(user_log) as log_capture: user_strategy.init() else: user_strategy.init() if config.extra.context_vars: for k, v in six.iteritems(config.extra.context_vars): if isinstance(v, RqAttrDict): v = v.__dict__ setattr(ucontext, k, v) if persist_helper: env.event_bus.publish_event(Event(EVENT.BEFORE_SYSTEM_RESTORED)) if persist_helper.restore(None): user_system_log.info(_('system restored')) else: log_capture.replay() env.event_bus.publish_event(Event(EVENT.POST_SYSTEM_RESTORED)) init_succeed = True bar_dict = BarMap(env.data_proxy, config.base.frequency) executor.run(bar_dict) env.event_bus.publish_event(Event(EVENT.POST_STRATEGY_RUN)) if env.profile_deco: output_profile_result(env) except CustomException as e: if init_succeed and persist_helper and env.config.base.persist_mode == const.PERSIST_MODE.ON_CRASH: persist_helper.persist() code = _exception_handler(e) mod_handler.tear_down(code, e) except Exception as e: if init_succeed and persist_helper and env.config.base.persist_mode == const.PERSIST_MODE.ON_CRASH: persist_helper.persist() exc_type, exc_val, exc_tb = sys.exc_info() user_exc = create_custom_exception(exc_type, exc_val, exc_tb, config.base.strategy_file) code = _exception_handler(user_exc) mod_handler.tear_down(code, user_exc) else: if persist_helper and env.config.base.persist_mode == const.PERSIST_MODE.ON_NORMAL_EXIT: persist_helper.persist() result = mod_handler.tear_down(const.EXIT_CODE.EXIT_SUCCESS) system_log.debug(_(u"strategy run successfully, normal exit")) return result
def handle_tick(self, event): tick = event.tick with ExecutionContext(EXECUTION_PHASE.ON_TICK): with ModifyExceptionFromType(EXC_TYPE.USER_EXC): self._handle_tick(self._user_context, tick)
def open_auction(self, event): bar_dict = event.bar_dict with ExecutionContext(EXECUTION_PHASE.OPEN_AUCTION): with ModifyExceptionFromType(EXC_TYPE.USER_EXC): self._open_auction(self._user_context, bar_dict)
def run(config, source_code=None, user_funcs=None): env = Environment(config) persist_helper = None init_succeed = False mod_handler = ModHandler() try: # avoid register handlers everytime # when running in ipython set_loggers(config) basic_system_log.debug("\n" + pformat(config.convert_to_dict())) env.set_strategy_loader( init_strategy_loader(env, source_code, user_funcs, config)) env.set_global_vars(GlobalVars()) mod_handler.set_env(env) mod_handler.start_up() try: future_info = config.base.future_info except AttributeError: pass else: deep_update(future_info, future_info_cn.CN_FUTURE_INFO) if not env.data_source: env.set_data_source(BaseDataSource(config.base.data_bundle_path)) if env.price_board is None: from .core.bar_dict_price_board import BarDictPriceBoard env.price_board = BarDictPriceBoard() env.set_data_proxy(DataProxy(env.data_source, env.price_board)) Scheduler.set_trading_dates_(env.data_source.get_trading_calendar()) scheduler = Scheduler(config.base.frequency) mod_scheduler._scheduler = scheduler env._universe = StrategyUniverse() _adjust_start_date(env.config, env.data_proxy) # FIXME start_dt = datetime.datetime.combine(config.base.start_date, datetime.datetime.min.time()) env.calendar_dt = start_dt env.trading_dt = start_dt broker = env.broker assert broker is not None env.portfolio = broker.get_portfolio() if env.benchmark_provider: env.benchmark_portfolio = BenchmarkPortfolio( env.benchmark_provider, env.portfolio.units) event_source = env.event_source assert event_source is not None bar_dict = BarMap(env.data_proxy, config.base.frequency) env.set_bar_dict(bar_dict) ctx = ExecutionContext(const.EXECUTION_PHASE.GLOBAL) ctx._push() env.event_bus.publish_event(Event(EVENT.POST_SYSTEM_INIT)) scope = create_base_scope(config.base.run_type == RUN_TYPE.BACKTEST) scope.update({"g": env.global_vars}) apis = api_helper.get_apis() scope.update(apis) scope = env.strategy_loader.load(scope) if env.config.extra.enable_profiler: enable_profiler(env, scope) ucontext = StrategyContext() scheduler.set_user_context(ucontext) from .core.executor import Executor executor = Executor(env) persist_helper = init_persist_helper(env, scheduler, ucontext, executor, config) if persist_helper: should_resume = persist_helper.should_resume() should_run_init = persist_helper.should_run_init() else: should_resume = False should_run_init = True user_strategy = Strategy(env.event_bus, scope, ucontext, should_run_init) env.user_strategy = user_strategy if (should_resume and not should_run_init) or not should_resume: with run_with_user_log_disabled(disabled=should_resume): user_strategy.init() if config.extra.context_vars: for k, v in six.iteritems(config.extra.context_vars): if isinstance(v, RqAttrDict): v = v.__dict__ setattr(ucontext, k, v) if persist_helper: env.event_bus.publish_event(Event(EVENT.BEFORE_SYSTEM_RESTORED)) env.event_bus.publish_event(Event(EVENT.DO_RESTORE)) env.event_bus.publish_event(Event(EVENT.POST_SYSTEM_RESTORED)) init_succeed = True if should_resume and should_run_init: user_strategy.init() executor.run(bar_dict) if env.profile_deco: output_profile_result(env) except CustomException as e: if init_succeed and persist_helper and env.config.base.persist_mode == const.PERSIST_MODE.ON_CRASH: persist_helper.persist() code = _exception_handler(e) mod_handler.tear_down(code, e) except Exception as e: if init_succeed and persist_helper and env.config.base.persist_mode == const.PERSIST_MODE.ON_CRASH: persist_helper.persist() exc_type, exc_val, exc_tb = sys.exc_info() user_exc = create_custom_exception(exc_type, exc_val, exc_tb, config.base.strategy_file) code = _exception_handler(user_exc) mod_handler.tear_down(code, user_exc) else: if persist_helper and env.config.base.persist_mode == const.PERSIST_MODE.ON_NORMAL_EXIT: persist_helper.persist() result = mod_handler.tear_down(const.EXIT_CODE.EXIT_SUCCESS) system_log.debug(_(u"strategy run successfully, normal exit")) return result
def history_bars(order_book_id, bar_count, frequency, fields=None, skip_suspended=True, include_now=False, adjust_type='pre'): """ 获取指定合约的历史行情,同时支持日以及分钟历史数据。不能在init中调用。 注意,该API会自动跳过停牌数据。 日回测获取分钟历史数据:不支持 日回测获取日历史数据 ========================= =================================================== 调用时间 返回数据 ========================= =================================================== T日before_trading T-1日day bar T日handle_bar T日day bar ========================= =================================================== 分钟回测获取日历史数据 ========================= =================================================== 调用时间 返回数据 ========================= =================================================== T日before_trading T-1日day bar T日handle_bar T-1日day bar ========================= =================================================== 分钟回测获取分钟历史数据 ========================= =================================================== 调用时间 返回数据 ========================= =================================================== T日before_trading T-1日最后一个minute bar T日handle_bar T日当前minute bar ========================= =================================================== :param order_book_id: 合约代码 :type order_book_id: `str` :param int bar_count: 获取的历史数据数量,必填项 :param str frequency: 获取数据什么样的频率进行。'1d'或'1m'分别表示每日和每分钟,必填项 :param str fields: 返回数据字段。必填项。见下方列表。 ========================= =================================================== fields 字段名 ========================= =================================================== datetime 时间戳 open 开盘价 high 最高价 low 最低价 close 收盘价 volume 成交量 total_turnover 成交额 open_interest 持仓量(期货专用) basis_spread 期现差(股指期货专用) settlement 结算价(期货日线专用) prev_settlement 结算价(期货日线专用) ========================= =================================================== :param bool skip_suspended: 是否跳过停牌数据 :param bool include_now: 是否包含当前数据 :param str adjust_type: 复权类型,默认为前复权 pre;可选 pre, none, post :return: `ndarray`, 方便直接与talib等计算库对接,效率较history返回的DataFrame更高。 :example: 获取最近5天的日线收盘价序列(策略当前日期为20160706): .. code-block:: python3 :linenos: [In] logger.info(history_bars('000002.XSHE', 5, '1d', 'close')) [Out] [ 8.69 8.7 8.71 8.81 8.81] """ order_book_id = assure_order_book_id(order_book_id) env = Environment.get_instance() dt = env.calendar_dt if frequency[-1] == 'm' and env.config.base.frequency == '1d': raise RQInvalidArgument('can not get minute history in day back test') if adjust_type not in {'pre', 'post', 'none'}: raise RuntimeError('invalid adjust_type') if frequency == '1d': sys_frequency = Environment.get_instance().config.base.frequency if ((sys_frequency in ['1m', 'tick'] and not include_now) or ExecutionContext.phase() == EXECUTION_PHASE.BEFORE_TRADING): dt = env.data_proxy.get_previous_trading_date( env.trading_dt.date()) # 当 EXECUTION_PHASE.BEFORE_TRADING 的时候,强制 include_now 为 False include_now = False if sys_frequency == "1d": # 日回测不支持 include_now include_now = False if fields is None: fields = ["datetime", "open", "high", "low", "close", "volume"] return env.data_proxy.history_bars(order_book_id, bar_count, frequency, fields, dt, skip_suspended=skip_suspended, include_now=include_now, adjust_type=adjust_type, adjust_orig=env.trading_dt)
def history_bars(order_book_id, bar_count, frequency, fields=None, skip_suspended=True, include_now=False, adjust_type='pre'): """ 获取指定合约的历史行情,同时支持日以及分钟历史数据。不能在init中调用。 注意,该API会自动跳过停牌数据。 日回测获取分钟历史数据:不支持 日回测获取日历史数据 ========================= =================================================== 调用时间 返回数据 ========================= =================================================== T日before_trading T-1日day bar T日handle_bar T日day bar ========================= =================================================== 分钟回测获取日历史数据 ========================= =================================================== 调用时间 返回数据 ========================= =================================================== T日before_trading T-1日day bar T日handle_bar T-1日day bar ========================= =================================================== 分钟回测获取分钟历史数据 ========================= =================================================== 调用时间 返回数据 ========================= =================================================== T日before_trading T-1日最后一个minute bar T日handle_bar T日当前minute bar ========================= =================================================== :param order_book_id: 合约代码 :type order_book_id: `str` :param int bar_count: 获取的历史数据数量,必填项 :param str frequency: 获取数据什么样的频率进行。'1d'或'1m'分别表示每日和每分钟,必填项 :param str fields: 返回数据字段。必填项。见下方列表。 ========================= =================================================== fields 字段名 ========================= =================================================== datetime 时间戳 open 开盘价 high 最高价 low 最低价 close 收盘价 volume 成交量 total_turnover 成交额 open_interest 持仓量(期货专用) basis_spread 期现差(股指期货专用) settlement 结算价(期货日线专用) prev_settlement 结算价(期货日线专用) ========================= =================================================== :param bool skip_suspended: 是否跳过停牌数据 :param bool include_now: 是否包含当前数据 :param str adjust_type: 复权类型,默认为前复权 pre;可选 pre, none, post :return: `ndarray`, 方便直接与talib等计算库对接,效率较history返回的DataFrame更高。 :example: 获取最近5天的日线收盘价序列(策略当前日期为20160706): .. code-block:: python3 :linenos: [In] logger.info(history_bars('000002.XSHE', 5, '1d', 'close')) [Out] [ 8.69 8.7 8.71 8.81 8.81] """ order_book_id = assure_order_book_id(order_book_id) env = Environment.get_instance() dt = env.calendar_dt if frequency[-1] not in {'m', 'd'}: raise RQInvalidArgument('invalid frequency {}'.format(frequency)) if frequency[-1] == 'm' and env.config.base.frequency == '1d': raise RQInvalidArgument('can not get minute history in day back test') if frequency[-1] == 'd' and frequency != '1d': raise RQInvalidArgument('invalid frequency') if adjust_type not in {'pre', 'post', 'none'}: raise RuntimeError('invalid adjust_type') if frequency == '1d': sys_frequency = Environment.get_instance().config.base.frequency if ((sys_frequency in ['1m', 'tick'] and not include_now) or ExecutionContext.phase() == EXECUTION_PHASE.BEFORE_TRADING): dt = env.data_proxy.get_previous_trading_date(env.trading_dt.date()) # 当 EXECUTION_PHASE.BEFORE_TRADING 的时候,强制 include_now 为 False include_now = False if sys_frequency == "1d": # 日回测不支持 include_now include_now = False if fields is None: fields = ["datetime", "open", "high", "low", "close", "volume"] return env.data_proxy.history_bars(order_book_id, bar_count, frequency, fields, dt, skip_suspended=skip_suspended, include_now=include_now, adjust_type=adjust_type, adjust_orig=env.trading_dt)